KLASIFIKASI DIABETES SUKU INDIAN PIMA MENGGUNAKAN KOMBINASI METODE RANDOM FOREST DAN NAIVE BAYES

LIANDRA, MUHAMMAD GHEDDI VIJAYA and Samsuryadi, Samsuryadi and Miraswan, Kanda Januar (2020) KLASIFIKASI DIABETES SUKU INDIAN PIMA MENGGUNAKAN KOMBINASI METODE RANDOM FOREST DAN NAIVE BAYES. Undergraduate thesis, Sriwijaya University.

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Abstract

Combined Random Forest and Naive Bayes method can produce better prediction accuracy. This study uses the combined Random Forest and Naive Bayes method to see whether the combined method will always produce better results than the individual method, or not. Based on the result of 280 test cases with Pima Indian diabetes dataset, the combined method only outperformed the accuracy of both the individual Random Forest and Naive Bayes method for 96 times, losing to Random Forest that outperformed the combined method and individual Naive Bayes method for 127 times.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Diabetes, Naive Bayes, Random Forest, Data Mining
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 3986 not found.
Date Deposited:	18 Aug 2020 04:13
Last Modified:	18 Aug 2020 04:13
URI:	http://repository.unsri.ac.id/id/eprint/33259

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